Reinforcement Learning (RL) is a field of AI where agents learn to make decisions through trial-and-error to maximize rewards. This course covers core RL concepts, algorithms, and applications, including Q-Learning, Deep RL, and policy-based methods, with hands-on experience to solve real-world problems in robotics, games, and recommendation systems.
Reinforcement Learning (RL) is a field of AI where agents learn to make decisions through trial-and-error to maximize rewards. This course covers core RL concepts, algorithms, and applications, including Q-Learning, Deep RL, and policy-based methods, with hands-on experience to solve real-world problems in robotics, games, and recommendation systems.
